Name
Title | ||
|---|---|---|
Spatially Adaptive Wavelet-Based Method Using the Cauchy Prior for Denoising the SAR Images |
Abstract | ||
|---|---|---|
The speckle noise complicates the human and automatic interpretation of synthetic aperture radar (SAR) images. Thus, the reduction of speckle is critical in various SAR image processing tasks. In this paper, we introduce a new spatially adaptive wavelet-based Bayesian method for despeckling the SAR images. The wavelet coefficients of the logarithmically transformed reflectance and speckle noise are modeled using the zero-location Cauchy and zero-mean Gaussian distributions, respectively. These prior distributions are then exploited to develop a Bayesian minimum mean absolute error estimator as well as a maximum a posteriori estimator. A new context-based technique with a reduced complexity is proposed for incorporating the spatial dependency of the wavelet coefficients with the Bayesian estimation processes. Experiments are carried out using typical noise-free images corrupted with simulated speckle noise as well as real SAR images, and the results show that the proposed method performs favorably in comparison to some of the existing methods in terms of the peak signal-to-noise ratio, speckle statistics and structural similarity index, and in its ability to suppress the speckle in the homogeneous regions |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TCSVT.2006.888020 | IEEE Trans. Circuits Syst. Video Techn. |
Keywords | Field | DocType |
spatially adaptive wavelet-based method,simulated speckle noise,speckle noise,real sar image,speckle statistic,sar image,wavelet coefficient,various sar image processing,sar images,bayesian minimum,bayesian method,bayesian estimation process,prior distribution,psnr,synthetic aperture radar,wavelet transform,wavelet transforms,image processing,radar imaging,reflectivity,cauchy distribution,gaussian noise,speckle,spatial dependence,mean absolute error,peak signal to noise ratio,gaussian distribution,structural similarity,maximum likelihood estimation,noise reduction,bayesian methods | Radar imaging,Speckle pattern,Pattern recognition,Computer science,Synthetic aperture radar,Image processing,Artificial intelligence,Speckle noise,Bayes estimator,Wavelet transform,Wavelet | Journal |
Volume | Issue | ISSN |
17 | 4 | 1051-8215 |
Citations | PageRank | References |
34 | 1.65 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. I.H. Bhuiyan | 1 | 58 | 2.88 |
| M. O. Ahmad | 2 | 1157 | 154.87 |
| M. N.S. Swamy | 3 | 267 | 18.50 |